auto tensor shape and channels handling

dist/human.esm-nobundle.js

@@ -1006,13 +1006,34 @@ async function process2(input, config3, getTensor = true) {
     throw new Error("input type is not recognized");
   }
   if (input instanceof Tensor) {
-    if (input["isDisposedInternal"]) {
+    let tensor3 = null;
+    if (input["isDisposedInternal"])
       throw new Error("input tensor is disposed");
-    } else if (!input.shape || input.shape.length !== 4 || input.shape[0] !== 1 || input.shape[3] !== 3) {
+    if (!input["shape"])
-      throw new Error("input tensor shape must be [1, height, width, 3] and instead was" + (input["shape"] ? input["shape"].toString() : "unknown"));
+      throw new Error("input tensor has no shape");
-    } else {
+    if (input.shape.length === 3) {
-      return { tensor: tfjs_esm_exports.clone(input), canvas: config3.filter.return ? outCanvas : null };
+      if (input.shape[2] === 3) {
+        tensor3 = tfjs_esm_exports.expandDims(input, 0);
+      } else if (input.shape[2] === 4) {
+        const rgb2 = tfjs_esm_exports.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        tensor3 = tfjs_esm_exports.expandDims(rgb2, 0);
+        tfjs_esm_exports.dispose(rgb2);
+      }
+    } else if (input.shape.length === 4) {
+      if (input.shape[3] === 3) {
+        tensor3 = tfjs_esm_exports.clone(input);
+      } else if (input.shape[3] === 4) {
+        tensor3 = tfjs_esm_exports.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3)
+      throw new Error(`could not process input tensor with shape: ${input["shape"]}`);
+    if (tensor3.dtype === "int32") {
+      const cast5 = tfjs_esm_exports.cast(tensor3, "float32");
+      tfjs_esm_exports.dispose(tensor3);
+      tensor3 = cast5;
+    }
+    return { tensor: tensor3, canvas: config3.filter.return ? outCanvas : null };
   } else {
     if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
       if (config3.debug)

dist/human.esm.js

@@ -71331,13 +71331,34 @@ async function process2(input2, config3, getTensor2 = true) {
     throw new Error("input type is not recognized");
   }
   if (input2 instanceof Tensor) {
-    if (input2["isDisposedInternal"]) {
+    let tensor2 = null;
+    if (input2["isDisposedInternal"])
       throw new Error("input tensor is disposed");
-    } else if (!input2.shape || input2.shape.length !== 4 || input2.shape[0] !== 1 || input2.shape[3] !== 3) {
+    if (!input2["shape"])
-      throw new Error("input tensor shape must be [1, height, width, 3] and instead was" + (input2["shape"] ? input2["shape"].toString() : "unknown"));
+      throw new Error("input tensor has no shape");
-    } else {
+    if (input2.shape.length === 3) {
-      return { tensor: clone(input2), canvas: config3.filter.return ? outCanvas : null };
+      if (input2.shape[2] === 3) {
+        tensor2 = expandDims(input2, 0);
+      } else if (input2.shape[2] === 4) {
+        const rgb2 = slice3d(input2, [0, 0, 0], [-1, -1, 3]);
+        tensor2 = expandDims(rgb2, 0);
+        dispose(rgb2);
+      }
+    } else if (input2.shape.length === 4) {
+      if (input2.shape[3] === 3) {
+        tensor2 = clone(input2);
+      } else if (input2.shape[3] === 4) {
+        tensor2 = slice4d(input2, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    if (tensor2 == null || tensor2.shape.length !== 4 || tensor2.shape[0] !== 1 || tensor2.shape[3] !== 3)
+      throw new Error(`could not process input tensor with shape: ${input2["shape"]}`);
+    if (tensor2.dtype === "int32") {
+      const cast7 = cast(tensor2, "float32");
+      dispose(tensor2);
+      tensor2 = cast7;
+    }
+    return { tensor: tensor2, canvas: config3.filter.return ? outCanvas : null };
   } else {
     if (typeof input2["readyState"] !== "undefined" && input2["readyState"] <= 2) {
       if (config3.debug)

dist/human.node-gpu.js

@@ -1016,13 +1016,34 @@ async function process2(input, config3, getTensor = true) {
     throw new Error("input type is not recognized");
   }
   if (input instanceof tf2.Tensor) {
-    if (input["isDisposedInternal"]) {
+    let tensor3 = null;
+    if (input["isDisposedInternal"])
       throw new Error("input tensor is disposed");
-    } else if (!input.shape || input.shape.length !== 4 || input.shape[0] !== 1 || input.shape[3] !== 3) {
+    if (!input["shape"])
-      throw new Error("input tensor shape must be [1, height, width, 3] and instead was" + (input["shape"] ? input["shape"].toString() : "unknown"));
+      throw new Error("input tensor has no shape");
-    } else {
+    if (input.shape.length === 3) {
-      return { tensor: tf2.clone(input), canvas: config3.filter.return ? outCanvas : null };
+      if (input.shape[2] === 3) {
+        tensor3 = tf2.expandDims(input, 0);
+      } else if (input.shape[2] === 4) {
+        const rgb2 = tf2.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        tensor3 = tf2.expandDims(rgb2, 0);
+        tf2.dispose(rgb2);
+      }
+    } else if (input.shape.length === 4) {
+      if (input.shape[3] === 3) {
+        tensor3 = tf2.clone(input);
+      } else if (input.shape[3] === 4) {
+        tensor3 = tf2.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3)
+      throw new Error(`could not process input tensor with shape: ${input["shape"]}`);
+    if (tensor3.dtype === "int32") {
+      const cast5 = tf2.cast(tensor3, "float32");
+      tf2.dispose(tensor3);
+      tensor3 = cast5;
+    }
+    return { tensor: tensor3, canvas: config3.filter.return ? outCanvas : null };
   } else {
     if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
       if (config3.debug)

dist/human.node-wasm.js

@@ -1017,13 +1017,34 @@ async function process2(input, config3, getTensor = true) {
     throw new Error("input type is not recognized");
   }
   if (input instanceof tf2.Tensor) {
-    if (input["isDisposedInternal"]) {
+    let tensor3 = null;
+    if (input["isDisposedInternal"])
       throw new Error("input tensor is disposed");
-    } else if (!input.shape || input.shape.length !== 4 || input.shape[0] !== 1 || input.shape[3] !== 3) {
+    if (!input["shape"])
-      throw new Error("input tensor shape must be [1, height, width, 3] and instead was" + (input["shape"] ? input["shape"].toString() : "unknown"));
+      throw new Error("input tensor has no shape");
-    } else {
+    if (input.shape.length === 3) {
-      return { tensor: tf2.clone(input), canvas: config3.filter.return ? outCanvas : null };
+      if (input.shape[2] === 3) {
+        tensor3 = tf2.expandDims(input, 0);
+      } else if (input.shape[2] === 4) {
+        const rgb2 = tf2.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        tensor3 = tf2.expandDims(rgb2, 0);
+        tf2.dispose(rgb2);
+      }
+    } else if (input.shape.length === 4) {
+      if (input.shape[3] === 3) {
+        tensor3 = tf2.clone(input);
+      } else if (input.shape[3] === 4) {
+        tensor3 = tf2.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3)
+      throw new Error(`could not process input tensor with shape: ${input["shape"]}`);
+    if (tensor3.dtype === "int32") {
+      const cast5 = tf2.cast(tensor3, "float32");
+      tf2.dispose(tensor3);
+      tensor3 = cast5;
+    }
+    return { tensor: tensor3, canvas: config3.filter.return ? outCanvas : null };
   } else {
     if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
       if (config3.debug)

dist/human.node.js

@@ -1016,13 +1016,34 @@ async function process2(input, config3, getTensor = true) {
     throw new Error("input type is not recognized");
   }
   if (input instanceof tf2.Tensor) {
-    if (input["isDisposedInternal"]) {
+    let tensor3 = null;
+    if (input["isDisposedInternal"])
       throw new Error("input tensor is disposed");
-    } else if (!input.shape || input.shape.length !== 4 || input.shape[0] !== 1 || input.shape[3] !== 3) {
+    if (!input["shape"])
-      throw new Error("input tensor shape must be [1, height, width, 3] and instead was" + (input["shape"] ? input["shape"].toString() : "unknown"));
+      throw new Error("input tensor has no shape");
-    } else {
+    if (input.shape.length === 3) {
-      return { tensor: tf2.clone(input), canvas: config3.filter.return ? outCanvas : null };
+      if (input.shape[2] === 3) {
+        tensor3 = tf2.expandDims(input, 0);
+      } else if (input.shape[2] === 4) {
+        const rgb2 = tf2.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        tensor3 = tf2.expandDims(rgb2, 0);
+        tf2.dispose(rgb2);
+      }
+    } else if (input.shape.length === 4) {
+      if (input.shape[3] === 3) {
+        tensor3 = tf2.clone(input);
+      } else if (input.shape[3] === 4) {
+        tensor3 = tf2.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    if (tensor3 == null || tensor3.shape.length !== 4 || tensor3.shape[0] !== 1 || tensor3.shape[3] !== 3)
+      throw new Error(`could not process input tensor with shape: ${input["shape"]}`);
+    if (tensor3.dtype === "int32") {
+      const cast5 = tf2.cast(tensor3, "float32");
+      tf2.dispose(tensor3);
+      tensor3 = cast5;
+    }
+    return { tensor: tensor3, canvas: config3.filter.return ? outCanvas : null };
   } else {
     if (typeof input["readyState"] !== "undefined" && input["readyState"] <= 2) {
       if (config3.debug)

src/image/image.ts

@@ -77,15 +77,33 @@ export async function process(input: Input, config: Config, getTensor: boolean =
   ) {
     throw new Error('input type is not recognized');
   }
-  if (input instanceof tf.Tensor) {
+  if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed
-    // if input is tensor, use as-is
+    let tensor: Tensor | null = null;
-    if ((input)['isDisposedInternal']) {
+    if ((input as Tensor)['isDisposedInternal']) throw new Error('input tensor is disposed');
-      throw new Error('input tensor is disposed');
+    if (!(input as Tensor)['shape']) throw new Error('input tensor has no shape');
-    } else if (!(input as Tensor).shape || (input as Tensor).shape.length !== 4 || (input as Tensor).shape[0] !== 1 || (input as Tensor).shape[3] !== 3) {
+    if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]
-      throw new Error('input tensor shape must be [1, height, width, 3] and instead was' + (input['shape'] ? input['shape'].toString() : 'unknown'));
+      if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch
-    } else {
+        tensor = tf.expandDims(input, 0);
-      return { tensor: tf.clone(input), canvas: (config.filter.return ? outCanvas : null) };
+      } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch
+        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);
+        tensor = tf.expandDims(rgb, 0);
+        tf.dispose(rgb);
+      }
+    } else if ((input as Tensor).shape.length === 4) { // [1, width, height, 3 || 4]
+      if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone
+        tensor = tf.clone(input);
+      } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha
+        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);
+      }
     }
+    // at the end shape must be [1, height, width, 3]
+    if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`could not process input tensor with shape: ${input['shape']}`);
+    if ((tensor as Tensor).dtype === 'int32') {
+      const cast = tf.cast(tensor, 'float32');
+      tf.dispose(tensor);
+      tensor = cast;
+    }
+    return { tensor, canvas: (config.filter.return ? outCanvas : null) };
   } else {
     // check if resizing will be needed
     if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {

test/build.log

@@ -1,26 +1,26 @@
-2021-11-09 18:09:34 INFO:  @vladmandic/human version 2.5.1 
+2021-11-09 19:33:44 INFO:  @vladmandic/human version 2.5.1 
-2021-11-09 18:09:34 INFO:  User: vlado Platform: linux Arch: x64 Node: v17.0.1 
+2021-11-09 19:33:44 INFO:  User: vlado Platform: linux Arch: x64 Node: v17.0.1 
-2021-11-09 18:09:34 INFO:  Application: {"name":"@vladmandic/human","version":"2.5.1"} 
+2021-11-09 19:33:44 INFO:  Application: {"name":"@vladmandic/human","version":"2.5.1"} 
-2021-11-09 18:09:34 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2021-11-09 19:33:44 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2021-11-09 18:09:34 INFO:  Toolchain: {"build":"0.6.3","esbuild":"0.13.12","typescript":"4.4.4","typedoc":"0.22.8","eslint":"8.2.0"} 
+2021-11-09 19:33:44 INFO:  Toolchain: {"build":"0.6.3","esbuild":"0.13.12","typescript":"4.4.4","typedoc":"0.22.8","eslint":"8.2.0"} 
-2021-11-09 18:09:34 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2021-11-09 19:33:44 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2021-11-09 18:09:34 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 
+2021-11-09 19:33:44 STATE: Clean: {"locations":["dist/*","types/*","typedoc/*"]} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1275} 
+2021-11-09 19:33:44 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":1275} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":57,"inputBytes":526408,"outputBytes":444881} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":57,"inputBytes":527426,"outputBytes":445566} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1283} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":1283} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":57,"inputBytes":526416,"outputBytes":444885} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":57,"inputBytes":527434,"outputBytes":445570} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1350} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":1350} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":57,"inputBytes":526483,"outputBytes":444957} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":57,"inputBytes":527501,"outputBytes":445642} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1652} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1063,"outputBytes":1652} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2326,"outputBytes":912} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2326,"outputBytes":912} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":57,"inputBytes":526045,"outputBytes":446888} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":57,"inputBytes":527063,"outputBytes":447664} 
-2021-11-09 18:09:34 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2562703,"outputBytes":2497652} 
+2021-11-09 19:33:45 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":2562703,"outputBytes":2497652} 
-2021-11-09 18:09:35 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":57,"inputBytes":3022785,"outputBytes":1614549} 
+2021-11-09 19:33:46 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":57,"inputBytes":3023803,"outputBytes":1614837} 
-2021-11-09 18:09:35 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":57,"inputBytes":3022785,"outputBytes":2950223} 
+2021-11-09 19:33:46 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":57,"inputBytes":3023803,"outputBytes":2950885} 
-2021-11-09 18:09:55 STATE: Typings: {"input":"src/human.ts","output":"types","files":50} 
+2021-11-09 19:34:06 STATE: Typings: {"input":"src/human.ts","output":"types","files":50} 
-2021-11-09 18:10:02 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":49,"generated":true} 
+2021-11-09 19:34:13 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":49,"generated":true} 
-2021-11-09 18:10:02 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5801,"outputBytes":3822} 
+2021-11-09 19:34:13 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":5801,"outputBytes":3822} 
-2021-11-09 18:10:02 STATE: Compile: {"name":"demo/facerecognition","format":"esm","platform":"browser","input":"demo/facerecognition/index.ts","output":"demo/facerecognition/index.js","files":1,"inputBytes":8949,"outputBytes":6529} 
+2021-11-09 19:34:13 STATE: Compile: {"name":"demo/facerecognition","format":"esm","platform":"browser","input":"demo/facerecognition/index.ts","output":"demo/facerecognition/index.js","files":1,"inputBytes":8949,"outputBytes":6529} 
-2021-11-09 18:10:41 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":91,"errors":0,"warnings":0} 
+2021-11-09 19:34:48 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":91,"errors":0,"warnings":0} 
-2021-11-09 18:10:42 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2021-11-09 19:34:48 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2021-11-09 18:10:42 INFO:  Done... 
+2021-11-09 19:34:48 INFO:  Done... 

test/test-main.js

@@ -27,7 +27,7 @@ async function testHTTP() {
   });
 }
 
-async function getImage(human, input) {
+async function getImage(human, input, options = { channels: 3, expand: true, cast: true }) {
   let img;
   try {
     img = await canvasJS.loadImage(input);
@@ -39,18 +39,15 @@ async function getImage(human, input) {
   const ctx = canvas.getContext('2d');
   ctx.drawImage(img, 0, 0, img.width, img.height);
   const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
-  const res = human.tf.tidy(() => {
+
-    const tensor = human.tf.tensor(Array.from(imageData.data), [canvas.height, canvas.width, 4], 'float32'); // create rgba image tensor from flat array
+  const data = human.tf.tensor(Array.from(imageData.data), [canvas.height, canvas.width, 4], options.cast ? 'float32' : 'int32'); // create rgba image tensor from flat array
-    const channels = human.tf.split(tensor, 4, 2); // split rgba to channels
+  const channels = options.channels === 3 ? human.tf.slice3d(data, [0, 0, 0], [-1, -1, 3]) : human.tf.clone(data); // optionally strip alpha channel
-    const rgb = human.tf.stack([channels[0], channels[1], channels[2]], 2); // stack channels back to rgb
+  const tensor = options.expand ? human.tf.expandDims(channels, 0) : human.tf.clone(channels); // optionally add batch num dimension
-    const reshape = human.tf.reshape(rgb, [1, canvas.height, canvas.width, 3]); // move extra dim from the end of tensor and use it as batch number instead
+  human.tf.dispose([data, channels]);
-    return reshape;
+  const sum = human.tf.sum(tensor);
-  });
+  log('state', 'passed: load image:', input, tensor.shape, { checksum: sum.dataSync()[0] });
-  const sum = human.tf.sum(res);
-  if (res && res.shape[0] === 1 && res.shape[3] === 3) log('state', 'passed: load image:', input, res.shape, { checksum: sum.dataSync()[0] });
-  else log('error', 'failed: load image:', input, res);
   human.tf.dispose(sum);
-  return res;
+  return tensor;
 }
 
 function printResults(detect) {
@@ -96,8 +93,6 @@ async function testWarmup(human, title) {
   }
   if (warmup) {
     log('state', 'passed: warmup:', config.warmup, title);
-    // const count = human.tf.engine().state.numTensors;
-    // if (count - tensors > 0) log('warn', 'failed: memory', config.warmup, title, 'tensors:', count - tensors);
     printResults(warmup);
   } else {
     log('error', 'failed: warmup:', config.warmup, title);
@@ -176,6 +171,41 @@ async function verifyDetails(human) {
   }
 }
 
+async function testTensorShapes(human, input) {
+  await human.load(config);
+  const numTensors = human.tf.engine().state.numTensors;
+  let res;
+  let tensor;
+
+  tensor = await getImage(human, input, { channels: 4, expand: true, cast: true });
+  res = await human.detect(tensor, config);
+  verify(res.face.length === 1 && res.face[0].gender === 'female', 'tensor shape:', tensor.shape, 'dtype:', tensor.dtype);
+  human.tf.dispose(tensor);
+
+  tensor = await getImage(human, input, { channels: 4, expand: false, cast: true });
+  res = await human.detect(tensor, config);
+  verify(res.face.length === 1 && res.face[0].gender === 'female', 'tensor shape:', tensor.shape, 'dtype:', tensor.dtype);
+  human.tf.dispose(tensor);
+
+  tensor = await getImage(human, input, { channels: 3, expand: true, cast: true });
+  res = await human.detect(tensor, config);
+  verify(res.face.length === 1 && res.face[0].gender === 'female', 'tensor shape:', tensor.shape, 'dtype:', tensor.dtype);
+  human.tf.dispose(tensor);
+
+  tensor = await getImage(human, input, { channels: 3, expand: false, cast: true });
+  res = await human.detect(tensor, config);
+  verify(res.face.length === 1 && res.face[0].gender === 'female', 'tensor shape:', tensor.shape, 'dtype:', tensor.dtype);
+  human.tf.dispose(tensor);
+
+  tensor = await getImage(human, input, { channels: 4, expand: true, cast: false });
+  res = await human.detect(tensor, config);
+  verify(res.face.length === 1 && res.face[0].gender === 'female', 'tensor shape:', tensor.shape, 'dtype:', tensor.dtype);
+  human.tf.dispose(tensor);
+
+  const leak = human.tf.engine().state.numTensors - numTensors;
+  if (leak !== 0) log('error', 'failed: memory leak', leak);
+}
+
 async function verifyCompare(human) {
   log('info', 'test: input compare');
   const t1 = await getImage(human, 'samples/in/ai-face.jpg');
@@ -253,6 +283,7 @@ async function test(Human, inputConfig) {
   });
 
   await verifyDetails(human);
+  await testTensorShapes(human, 'samples/in/ai-body.jpg');
 
   // test default config async
   log('info', 'test default');